查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1503364

2030 年金融科技市場人工智慧 (AI) 預測：按組件、部署模式、應用程式、最終用戶和地區進行的全球分析

Artificial Intelligence (AI) in Fintech Market Forecasts to 2030 - Global Analysis By Component (Solution, Services and Other Component), Deployment Mode, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，2024 年全球金融科技人工智慧 (AI) 市場規模將達到 440 億美元，預計到 2030 年將達到 586 億美元，在預測期內複合年成長率為 4.9%。

人工智慧 (AI) 透過提高各種金融服務的效率、個人化和安全性，正在徹底改變金融科技產業。人工智慧驅動的演算法可以快速分析大量資料，從而實現更好的風險評估、詐騙偵測和信用評分流程。在客戶服務方面，人工智慧聊天機器人和虛擬助理提供 24/7 全天候支持，改善用戶體驗並降低金融機構的營運成本。人工智慧演算法還透過識別市場資料的模式和趨勢來最佳化交易策略，以增強投資決策和投資組合管理。

根據認證詐欺審查員協會 (ACFE) 和分析先驅 SAS 進行的一項新民意調查，去年國際上使用人工智慧 (AI) 和機器學習 (ML) 進行詐欺檢測的情況有所增加。

更深入的客戶洞察和個性化

人工智慧可以分析大量客戶資料並了解客戶的財務行為、偏好和風險狀況。這使得金融科技機構能夠個人化金融產品和服務，提供有針對性的提案，並提高客戶滿意度。想像一下，收到根據您的風險接受度和貸款選擇量身定做的投資建議，並考慮到您獨特的財務狀況。

演算法決策偏差

人工智慧演算法可以使它們所訓練的資料中存在的偏見永久化。這可能導致歧視性貸款做法、不公平的風險評估或將某些群體排除在金融服務之外。仔細的資料選擇、偏差檢測技術和持續監控對於減少人工智慧主導的決策中阻礙市場成長的偏差至關重要。

提高效率和盈利

人工智慧可以自動執行傳統上由人類員工處理的繁瑣任務，例如貸款處理、詐欺偵測和客戶服務查詢。這簡化了業務，減少了人為錯誤，並釋放人力資本以專注於更具策略性的措施。效率的提高意味著金融科技公司成本的降低和利潤潛力的增加。這使得金融科技公司能夠即時偵測非法貿易，防止財務損失，並做出更明智的信用評估。

缺乏可解釋性和透明度

金融機構依賴人工智慧做出關鍵決策，例如信用評分、投資策略和詐欺檢測。然而，人工智慧模型固有的複雜性通常會導致黑盒流程，決策背後的基本原則不容易被相關人員（包括客戶、監管機構，甚至審核）理解或解釋。這種不透明性可能會導致一些負面影響。

COVID-19 的影響

由於許多零售商繼續面臨問題，COVID-19 的爆發影響了市場成長。許多商家推出了銷售點融資替代方案以實現潛在成長。商家像銀行帳戶一樣使用當前資料進行承保。這些公司還使用基於人工智慧的模型來了解基於交易和產品購買的消費行為。

在預測期內，服務業預計將是最大的。

託管服務預計將快速成長，因為它們有助於管理金融科技中支援人工智慧的應用程式，並有望成為預測期內最大的服務類別。金融科技新興企業正在利用人工智慧提供專業服務，預計將推動該產業的發展。糟糕的客戶服務或不正確的建議可能會導致客戶流失。虛擬助理和聊天機器人可以即時存取消費者的帳戶，提出個人化提案，並幫助他們管理儲蓄。專業服務可能有助於金融科技公司提供為消費者量身定做的 24/7 支持，同時減少誤導性建議、錯誤和糟糕客戶服務的可能性。

風險管理領域預計在預測期內複合年成長率最高。

由於人工智慧演算法處理敏感的財務資料並自動化決策流程，有效的風險管理實踐對於減輕潛在風險和確保監管合規性至關重要。此外，圍繞人工智慧在金融領域使用的法規審查需要遵守資料隱私法（例如 GDPR）和金融法規（例如巴塞爾協議 III），以及高度透明的人工智慧演算法和風險管理框架，以確保課責。

比最大的地區

由於著名的人工智慧軟體和系統供應商、金融機構對人工智慧計劃的聯合投資以及人工智慧在金融科技解決方案中的高度採用，預計北美在預測期內將佔據最大的市場佔有率。預計該地區在未來幾年該行業將出現顯著成長。此外，北美已成為許多人工智慧金融科技公司的業務中心，Sidetrade等公司選擇將北美業務設在卡加利，推動市場成長。

複合年成長率最高的地區：

由於政府的支持措施和國內企業的快速擴張為金融科技業務的人工智慧發展創造了許多機會，預計亞太地區在預測期內將保持最高的複合年成長率。此外，作為其業務策略的一部分，主要企業正在投資該地區的新市場，從而刺激該地區的市場成長。

免費客製化服務

訂閱此報告的客戶可以存取以下免費自訂選項之一：

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 家公司）
    • 主要企業SWOT分析（最多3家企業）
  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 研究資訊來源
    • 主要研究資訊來源
    • 二次研究資訊來源
    • 先決條件

第3章市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19 的影響

第4章波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章 全球金融科技人工智慧 (AI) 市場：按組成部分

  • 解決方案
    • 聊天機器人和虛擬助理
    • 詐欺檢測與預防
    • 信用評分和融資
    • 演算法交易
    • 個人化銀行業務
  • 服務
    • 管理服務
    • 支援與維護
    • 專業服務
    • 指南針諮詢
    • 實施和培訓
  • 其他組件

第6章 全球金融科技人工智慧（AI）市場：依部署模式

  • 雲
  • 本地

第7章 全球金融科技人工智慧 (AI) 市場：按應用分類

  • 危機管理
  • 付款及匯款
  • 客戶服務
  • 保險服務
  • 資產管理
  • 其他用途

第8章 全球金融科技人工智慧 (AI) 市場：按最終用戶分類

  • 銀行和金融機構
  • 保險公司
  • 投資公司
  • 金融科技Start-Ups
  • 其他最終用戶

第9章 全球金融科技人工智慧（AI）市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東/非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第10章 主要進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第11章 公司概況

  • Active.Ai
  • Amazon Web Services Inc.
  • Betterment Holdings
  • ComplyAdvantage.com
  • Data Minr Inc.
  • IBM Corporation
  • Intel Corporation
  • IPsoft Inc.
  • Microsoft Corporation
  • Narrative Science
  • Next IT Corporation
  • Onfido
  • Pefin Holdings LLC
  • Ripple Labs Inc.
  • Sift Science Inc.
  • TIBCO Software
  • Trifacta Software Inc.
  • WealthFront Inc.
  • Zeitgold
Product Code: SMRC26531

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Fintech Market is accounted for $44.0 billion in 2024 and is expected to reach $58.6 billion by 2030 growing at a CAGR of 4.9% during the forecast period. Artificial Intelligence (AI) is revolutionizing the Fintech industry by enhancing efficiency, personalization, and security across various financial services. AI-powered algorithms analyze vast amounts of data swiftly, enabling better risk assessment, fraud detection, and credit scoring processes. In customer service, AI-driven chatbots and virtual assistant's offer 24/7 support, improving user experience and reducing operational costs for financial institutions. AI algorithms also optimize trading strategies by identifying patterns and trends in market data, thereby enhancing investment decisions and portfolio management.

According to a new poll conducted by Certified Fraud Examiners (ACFE) and analytics pioneer SAS, the use of Artificial Intelligence (AI) and Machine Learning (ML) for fraud detection increased internationally last year.

Market Dynamics:

Driver:

Deeper customer insights and personalization

AI can analyze vast amounts of customer data to understand their financial behavior, preferences, and risk profiles. This enables Fintech institutions to personalize financial products and services, offer targeted recommendations, and improve customer satisfaction. Imagine receiving investment advice tailored to your risk tolerance or loan options that consider your unique financial situation.

Restraint:

Bias in algorithmic decisions

AI algorithms can perpetuate biases present in the data they are trained on. This can lead to discriminatory lending practices, unfair risk assessments, or exclusion of certain demographics from financial services. Careful data selection, bias detection techniques, and ongoing monitoring are essential to mitigate bias in AI-driven decisions hampering the growth of the market.

Opportunity:

Enhanced efficiency and profitability

AI automates tedious tasks traditionally handled by human employees, such as loan processing, fraud detection, and customer service inquiries. This streamlines operations, reduces manual errors, and frees up human capital to focus on more strategic initiatives. Improved efficiency translates to cost savings and potentially higher profits for Fintech companies. This empowers Fintech companies to detect fraudulent transactions in real-time, prevent financial losses, and make more informed creditworthiness assessments.

Threat:

Lack of explainability and transparency

Financial institutions rely on AI for critical decisions such as credit scoring, investment strategies, and fraud detection. However, the inherent complexity of AI models often results in black-box processes where the rationale behind decisions is not easily understandable or explainable to stakeholders, including customers, regulators, and even internal auditors. This opacity can lead to several adverse effects.

Covid-19 Impact

The outbreak of COVID 19 affected the market growth as many retailers continue to face problems. Many merchants implemented point of sale financing alternatives for potential growth. Merchants are using current data like a bank account for underwriting. Still, these players are also using AI-based models to access consumer behavior based on the transaction made or by their product purchase.

The services segment is expected to be the largest during the forecast period

The services is expected to be the largest during the forecast period as the managed service is likely to grow quickly owing to its help in administering AI-enabled apps in fintech. Fintech startups are using AI to provide professional services expected to drive the development of the segment. Poor customer service or incorrect advice might result in customer loss. Virtual assistants and chatbots can access consumers' accounts in real-time, provide personalized recommendations, and aid them in managing their savings. Professional services would assist fintech in providing tailored 24/7 support to their consumers while decreasing the likelihood of incorrect advice, errors, or bad customer service.

The risk management segment is expected to have the highest CAGR during the forecast period

The risk management segment is expected to have the highest CAGR during the forecast period as AI algorithms handle sensitive financial data and automate decision-making processes, effective risk management practices are essential to mitigate potential risks and ensure regulatory compliance. Moreover, regulatory scrutiny around AI usage in finance requires adherence to data privacy laws (like GDPR) and financial regulations (like Basel III), necessitating transparent AI algorithms and accountable risk management frameworks which encourage the growth of the market.

Region with largest share:

North America is projected to hold the largest market share during the forecast period due to prominent AI software and systems suppliers, combined investment by financial institutions into AI projects, and the adoption of most AI in Fintech solutions. The region is expected to experience significant growth in this area in the coming years. Additionally, North America serves as the business hub for many AI Fintech firms, with companies like Sidetrade choosing to locate their North American operations in Calgary which drives the market growth.

Region with highest CAGR:

Asia Pacific is projected to hold the highest CAGR over the forecast period owing the quick expansion of domestic firms with supportive government measures creates numerous opportunities for the advancement of AI in the fintech business. Furthermore, prominent players invest in the region's new markets as part of their business strategy, adding to regional market growth.

Key players in the market

Some of the key players in Artificial Intelligence (AI) in Fintech market include Active.Ai, Amazon Web Services Inc., Betterment Holdings, ComplyAdvantage.com, Data Minr Inc., IBM Corporation, Intel Corporation, IPsoft Inc., Microsoft Corporation, Narrative Science, Next IT Corporation, Onfido, Pefin Holdings LLC, Ripple Labs Inc., Sift Science Inc., TIBCO Software, Trifacta Software Inc., WealthFront Inc. and Zeitgold

Key Developments:

In June 2024, Intel Gaudi Enables a Lower Cost Alternative for AI Compute and GenAI. Community-based software simplifies generative AI (GenAI) development and industry-standard Ethernet networking enables flexible scaling of AI systems.

In February 2024, Indian startup Sarvam AI collaborates with Microsoft to bring its Indic voice large language model (LLM) to Azure. The collaboration aims to enable Sarvam AI to leverage Azure AI and Azure Infrastructure to build and deploy their voice LLM stack

Components Covered:

  • Solution
  • Services
  • Other Components

Deployment Modes Covered:

  • Cloud
  • On-Premise

Applications Covered:

  • Risk Management
  • Payments & Money Transfer
  • Customer Service
  • Insurance Services
  • Asset Management
  • Other Applications

End Users Covered:

  • Banks & Financial Institutions
  • Insurance Companies
  • Investment Firms
  • Fintech Startups
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence (AI) in Fintech Market, By Component

  • 5.1 Introduction
  • 5.2 Solution
    • 5.2.1 Chatbots & Virtual Assistants
    • 5.2.2 Fraud Detection & Prevention
    • 5.2.3 Credit Scoring & Lending
    • 5.2.4 Algorithmic Trading
    • 5.2.5 Personalized Banking
  • 5.3 Services
    • 5.3.1 Managed Services
    • 5.3.3 Support & Maintenance
    • 5.3.5 Professional Services
    • 5.3.7 Encompass Consulting
    • 5.3.9 Implementation & Training
  • 5.4 Other Component

6 Global Artificial Intelligence (AI) in Fintech Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Cloud
  • 6.3 On-Premise

7 Global Artificial Intelligence (AI) in Fintech Market, By Application

  • 7.1 Introduction
  • 7.2 Risk Management
  • 7.3 Payments & Money Transfer
  • 7.4 Customer Service
  • 7.5 Insurance Services
  • 7.6 Asset Management
  • 7.7 Other Applications

8 Global Artificial Intelligence (AI) in Fintech Market, By End User

  • 8.1 Introduction
  • 8.2 Banks & Financial Institutions
  • 8.3 Insurance Companies
  • 8.4 Investment Firms
  • 8.5 Fintech Startups
  • 8.6 Other End Users

9 Global Artificial Intelligence (AI) in Fintech Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Active.Ai
  • 11.2 Amazon Web Services Inc.
  • 11.3 Betterment Holdings
  • 11.4 ComplyAdvantage.com
  • 11.5 Data Minr Inc.
  • 11.6 IBM Corporation
  • 11.7 Intel Corporation
  • 11.8 IPsoft Inc.
  • 11.9 Microsoft Corporation
  • 11.10 Narrative Science
  • 11.11 Next IT Corporation
  • 11.12 Onfido
  • 11.13 Pefin Holdings LLC
  • 11.14 Ripple Labs Inc.
  • 11.15 Sift Science Inc.
  • 11.16 TIBCO Software
  • 11.17 Trifacta Software Inc.
  • 11.18 WealthFront Inc.
  • 11.19 Zeitgold

List of Tables

  • Table 1 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Region (2022-2030) ($MN)
  • Table 2 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Component (2022-2030) ($MN)
  • Table 3 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Solution (2022-2030) ($MN)
  • Table 4 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Chatbots & Virtual Assistants (2022-2030) ($MN)
  • Table 5 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Fraud Detection & Prevention (2022-2030) ($MN)
  • Table 6 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Credit Scoring & Lending (2022-2030) ($MN)
  • Table 7 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Algorithmic Trading (2022-2030) ($MN)
  • Table 8 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Personalized Banking (2022-2030) ($MN)
  • Table 9 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Services (2022-2030) ($MN)
  • Table 10 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Managed Services (2022-2030) ($MN)
  • Table 11 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Support & Maintenance (2022-2030) ($MN)
  • Table 12 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Professional Services (2022-2030) ($MN)
  • Table 13 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Encompass Consulting (2022-2030) ($MN)
  • Table 14 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Implementation & Training (2022-2030) ($MN)
  • Table 15 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Other Component (2022-2030) ($MN)
  • Table 16 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Deployment Mode (2022-2030) ($MN)
  • Table 17 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Cloud (2022-2030) ($MN)
  • Table 18 Global Artificial Intelligence (AI) in Fintech Market Outlook, By On-Premise (2022-2030) ($MN)
  • Table 19 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Application (2022-2030) ($MN)
  • Table 20 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Risk Management (2022-2030) ($MN)
  • Table 21 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Payments & Money Transfer (2022-2030) ($MN)
  • Table 22 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Customer Service (2022-2030) ($MN)
  • Table 23 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Insurance Services (2022-2030) ($MN)
  • Table 24 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Asset Management (2022-2030) ($MN)
  • Table 25 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 26 Global Artificial Intelligence (AI) in Fintech Market Outlook, By End User (2022-2030) ($MN)
  • Table 27 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Banks & Financial Institutions (2022-2030) ($MN)
  • Table 28 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Insurance Companies (2022-2030) ($MN)
  • Table 29 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Investment Firms (2022-2030) ($MN)
  • Table 30 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Fintech Startups (2022-2030) ($MN)
  • Table 31 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Other End Users (2022-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.